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Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu

Electrochemical CO 2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (–1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C–C coupling sites by themselves do not control selectivity to C 2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

30 DIRECT ENERGY CONVERSION↗

A bioactive supramolecular and covalent polymer scaffold for cartilage repair in a sheep model

Regeneration of hyaline cartilage in human-sized joints remains a clinical challenge, and it is a critical unmet need that would contribute to longer healthspans. Injectable scaffolds for cartilage repair that integrate both bioactivity and sufficiently robust physical properties to withstand joint stresses offer a promising strategy. We report here on a hybrid biomaterial that combines a bioactive peptide amphiphile supramolecular polymer that specifically binds the chondrogenic cytokine transforming growth factor β-1 (TGFβ-1) and crosslinked hyaluronic acid microgels that drive formation of filament bundles, a hierarchical motif common in natural musculoskeletal tissues. The scaffold is an injectable slurry that generates a porous rubbery material when exposed to calcium ions once placed in cartilage defects. The hybrid material was found to support in vitro chondrogenic differentiation of encapsulated stem cells in response to sustained delivery of TGFβ-1. Using a sheep model, we implanted the scaffold in shallow osteochondral defects and found it can remain localized in mechanically active joints. Evaluation of resected joints showed significantly improved repair of hyaline cartilage in osteochondral defects injected with the scaffold relative to defects injected with the growth factor alone, including implantation in the load-bearing femoral condyle. These results demonstrate the potential of the hybrid biomimetic scaffold as a niche to favor cartilage repair in mechanically active joints using a clinically relevant large-animal model.

Science & Technology - Other Topics↗

Nonequilibrium Diffusional Phase Transformations in Alloys Induced by Migration of Grain Boundaries and Dislocations

The main scenarios of nonequilibrium diffusional transformations induced by moving defects (dislocations, grain boundaries) in alloys under severe plastic deformation are considered. It has been shown that the phase state locally changes in the area of a defect where thermodynamic properties of alloy are locally changed, and the attained state is frozen after the displacement of a defect due to the difference between the rates of bulk diffusion and diffusion on a defect. For this reason, an alloy shifts from the state of its thermodynamic equilibrium under treatment, thus different nonequilibrium states, such as the disordering of alloy, the dissolution of equilibrium phase precipitates, the appearance of nonequilibrium phases, and the formation of regular structures, are possible depending on the type of the system. These effects may take place if the treatment of an alloy is performed at moderate temperatures, when diffusion is frozen in the bulk and rather active on defects. The phenomena of phase and structural instability developing under severe plastic deformation at moderate temperatures are considered within the framework of the proposed model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automatic Detection of Defects in High-Reliability Components

Disastrous consequences can result from defects in manufactured parts—particularly the high consequence parts developed at Sandia. Identifying flaws in as-built parts can be done with nondestructive means, such as X-ray Computed Tomography (CT). However, due to artifacts and complex imagery, the task of analyzing the CT images falls to humans. Human analysis is inherently unreproducible, unscalable, and can easily miss subtle flaws. We hypothesized that deep learning methods could improve defect identification, increase the number of parts that can effectively be analyzed, and do it in a reproducible manner. We pursued two methods: 1) generating a defect-free version of a scan and looking for differences (PandaNet), and 2) using pre-trained models to develop a statistical model of normality (Feature-based Anomaly Detection System: FADS). Both PandaNet and FADS provide good results, are scalable, and can identify anomalies in imagery. In particular, FADS enables zero-shot (training-free) identification of defects for minimal computational cost and expert time. It significantly outperforms prior approaches in computational cost while achieving comparable results. FADS’ core concept has also shown utility beyond anomaly detection by providing feature extraction for downstream tasks.

47 OTHER INSTRUMENTATION↗

Towards a Rational Model for the Triple Velocity Correlations of Turbulence

This paper presents a rational approach to modelling the triple velocity correlations that appear in the transport equations for the Reynolds stresses. All existing models of these correlations have largely been formulated on phenomenological grounds and are defective in one important aspect: they all neglect to allow for the dependence of these correlations on the local gradients of mean velocity. The mathematical necessity for this dependence will be demonstrated in the paper. The present contribution lies in the novel use of Group Representation Theory to determine the most general tensorial form of these correlations in terms of all the second- and third-order tensor quantities that appear in the exact equations that govern their evolution. The requisite representation did not exist in the literature and therefore had to be developed specifically for this purpose by Professor G. F. Smith. The outcome of this work is a mathematical framework for the construction of algebraic, explicit, and rational models for the triple velocity correlations that are theoretically consistent and include all the correct dependencies. Previous models are reviewed, and all are shown to be an incomplete subset of this new representation, even to lowest order.

Younis, B. A.↗

Defect Characterization of Monocrystalline Silicon Solar Cells with Polysilicon Passivated Contact Using Electrically-Detected Magnetic Resonance (EDMR) Spectroscopy

As the c-Si based solar cell efficiencies are approaching over 26%, it is becoming critical to characterize the low concentrations of the defects – as low as 10^10-10^11 cm-3 (for e.g., iron contamination in high-lifetime Ga-doped wafers3 and n-type wafers), and further reduce them. Also, atomistic level understanding of the mechanisms of the low concentration process-induced-defects and reliability limiting defects (such as light and elevated temperature induced degradation, surface passivation degradation) is needed to design the mitigation strategies. The conventional characterization techniques are limited due to their detection limitations. Some of the techniques based on lifetime spectroscopies can still be used for low concentration characterization however, they are based on estimations and theoretical models and hence, indirect and cannot fully reveal information about the microscopic mechanism of the defects. Thus, we present the application of an ultrasensitive magnetic resonance-based technique for the direct spectroscopic detection of the defects in Si PV - electrically detected magnetic resonance (EDMR). In this work, we aim to focus on establishing a process flow for fabrication of minicells with (miniature replica of the larger-area cells) and setting up the routine for EDMR measurements on them with the EDMR instrumentation capability at NREL. For the EDMR measurements, sample size is limited by the dimensions of sample holder tube (width less than 3.2 mm, active area - 20 mm). Thus, we have designed c-Si based minicells with polysilicon (poly-Si) passivated contacts same as the larger-area cells that we fabricate in our group at NREL. We also modified our minicell process flow for fabricating the textured minicells for preserving the texture during processing and taking care of the laser-ablation edge damage which can significantly affect the performance of such small devices. We have achieved comparable performance on these newly fabricated minicells as that of our 4 cm2 devices with same structure (comparable VOC, JSC, FF). We also conducted EDMR measurements on the minicells and observed a distinct EDMR signal at g-value ~2.005 at temperatures 30K and above, as shown in Fig. 2. We associate this signal to the presence of silicon dangling bonds based on the g-value. We also observed an EDMR signal at g-value ~1.998 at temperature ~5K. The origin of this signal is still being investigated. Thus, we show the proof of concept of minicells and EDMR measurements with which we now aim to study some of the unknown defects in silicon solar cell devices.

EDMR↗

Vision Algorithms Catch Defects in Screen Displays

Andrew Watson, a senior scientist at Ames Research Center, developed a tool called the Spatial Standard Observer (SSO), which models human vision for use in robotic applications. Redmond, Washington-based Radiant Zemax LLC licensed the technology from NASA and combined it with its imaging colorimeter system, creating a powerful tool that high-volume manufacturers of flat-panel displays use to catch defects in screens.

Source record↗

Automated calculation and convergence of defect transport tensors

Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.

36 MATERIALS SCIENCE↗

Comments on “Failure analysis of corroded hydrogen-blended natural gas pipelines based on finite element analysis and genetic algorithm-back propagation neural network” [262 (2025) 111174]

This is a brief commentary paper to highlight and discuss the determination of hydrogen concentration in pipeline steel, effect of hydrogen embrittlement (HE) on the mechanical properties of the material, burst strength of corroded pipelines using finite element analysis (FEA) simulations, and curve-fit models for assessing remaining strength of X80 corroded pipelines for transporting hydrogen blended natural gas. Recently, Xie et al. [1] proposed a methodology to quantify the impact of HE on material properties and numerically determined burst pressure of X80 corroded pipelines. However, their HE quantification overestimated the degradation of tensile strength for hydrogen blending ratios beyond the original data range, and their FEA results of burst pressure are nonconservative. This work thus recharacterized the hydrogen concentration in the steel pipeline and the effect of HE on tensile strength, and then redetermined burst pressures for a set of typical corrosion defect cases considered by Xie et al. [1] based on an experimentally validated FEA modelling method. With the new FEA results, two empirical corrosion models were proposed for X80 corroded pipelines for hydrogen service. At zero hydrogen blending ratio, the novel empirical models predict burst pressures to be consistent with the industry-accepted corrosion models. Furthermore, both the numerical simulation method and the novel corrosion models are significant contributions to the pipeline industry and the hydrogen community. Application of these results will enhance the safety, reliability, and integrity of natural gas pipelines when used to transport hydrogen.

Burst pressure prediction↗

Evaluation of Solid Modeling Software for Finite Element Analysis of Woven Ceramic Matrix Composites

Three computer programs, used for the purpose of generating 3-D finite element models of the Repeating Unit Cell (RUC) of a textile, were examined for suitability to model woven Ceramic Matrix Composites (CMCs). The programs evaluated were the open-source available TexGen, the commercially available WiseTex, and the proprietary Composite Material Evaluator (COMATE). A five-harness-satin (5HS) weave for a melt-infiltrated (MI) silicon carbide matrix and silicon carbide fiber was selected as an example problem and the programs were tested for their ability to generate a finite element model of the RUC. The programs were also evaluated for ease-of-use and capability, particularly for the capability to introduce various defect types such as porosity, ply shifting, and nesting of a laminate. Overall, it was found that TexGen and WiseTex were useful for generating solid models of the tow geometry; however, there was a lack of consistency in generating well-conditioned finite element meshes of the tows and matrix. TexGen and WiseTex were both capable of allowing collective and individual shifting of tows within a ply and WiseTex also had a ply nesting capability. TexGen and WiseTex were sufficiently userfriendly and both included a Graphical User Interface (GUI). COMATE was satisfactory in generating a 5HS finite element mesh of an idealized weave geometry but COMATE lacked a GUI and was limited to only 5HS and 8HS weaves compared to the larger amount of weave selections available with TexGen and WiseTex.

Nemeth, Noel N.↗

Temperature-dependent defect accumulation and evolution in Ni-irradiated NiFe concentrated solid-solution alloy

Temperature significantly affects defect migration and evolution in irradiated materials. However, the effects of temperature on defect evolution in concentrated solid-solution alloys (CSAs), including high entropy alloys, are not well understood, despite their potential as structural materials in advanced nuclear reactors. As an important model system of these CSAs, equiatomic Ni 50 Fe 50 (NiFe) was selected to understand the effects of temperature on defect evolution during irradiation and subsequent thermal annealing. Specifically, defect accumulation and evolution in NiFe alloy under Ni-ion irradiation at 150, 300, and 500 K were studied, and the irradiated specimens were subsequently annealed at higher temperatures. Rutherford backscattering spectrometry along the <100> channeling direction was employed to study damage accumulation and evolution before and after each irradiation and annealing experiment. Here we show that more defects survive and accumulate at 150 K, but more importantly defects can migrate to deeper depths at this low irradiation temperature. Irradiation-induced damage at 150 and 300 K does not recover substantially after post-irradiation annealing at 500 K, but dramatic recovery is observed after post-irradiation annealing at 700 K, indicating an onset temperature of defect recovery between 500 and 700 K. Here, the migration of irradiation-induced defects upon annealing is closely related to the mobility and stress state arising from the surviving defects. With the consideration of five stages of defect recovery in conventional dilute alloys, the underlying mechanisms for temperature-dependent defect accumulation and evolution in NiFe CSA are discussed.

36 MATERIALS SCIENCE↗

Crystal Structure and Atomic Vacancy Optimized Thermoelectric Properties in Gadolinium Selenides

Thermoelectric materials enable the energy conversion of waste heat into electricity, helpful to relieve global energy crisis. Here, we report a systematic investigation on high-temperature thermoelectric gadolinium selenides, cubic Gd 3-x Se 4 (x = 0.16, 0.21 and 0.25) and orthorhombic Gd 2 Se 3-y (y = 0.02, 0.06 and 0.08). High energy synchrotron x-ray diffraction and total scattering have been used to investigate the crystallographic and local structures. Atomic-scale clusters of Gd vacancy in the cubic phase are observed by employing the reverse Monte Carlo simulation. For cubic Gd 3-x Se 4 , adjusting Gd vacancy triggers the effect of multiple conduction bands, confirmed by the increase in effective masses and theoretical calculations. A reasonable peak zT value of 0.27 is achieved at 850 K for Gd 3-x Se 4 (x = 0.16). On the other hand, tuning Se vacancy enables the optimization of electron concentration for the orthorhombic Gd 2 Se 3-y . More significantly, its low deformation potential (Ξ = 12eV) gives rise to enhanced electron mobility and higher peak zT value of 0.54 at 850 K for Gd 2 Se 3-y (y = 0.02). Intriguingly, a higher zT of 1.2 at 1200 K is reasonably predicted by quality factor analysis. Finally, this work extends the scope of high-temperature thermoelectric materials and facilitates the exploration of novel high-temperature thermoelectric materials

36 MATERIALS SCIENCE↗

Size-Dependent Asymmetric Auger Interactions in Plasma-Produced n- and p-Type-Doped Silicon Nanocrystals

Nonradiative Auger recombination (AR) tends to dominate carrier dynamics in charged, quantum-confined structures. Consequently, it complicates the practical realization of many semiconductor nanocrystal (NC)-based devices such as light-emitting diodes, photovoltaic cells, and single-photon emitters, in which charged exciton states often occur. To this end, extensive experimental studies on direct band gap NCs have investigated the trion components (both positive and negative) that construct the total AR rate. However, such an analysis has remained elusive for indirect band gap Si NCs. In this study, we investigate AR decay of non-thermal plasma-produced n- and p-type-doped Si NCs. We expand the study over a large NC size range (D NC ~ 3-8 nm), in which n- and p-type doping is achieved by either a substitutional or surface doping effect, respectively. First, we monitor the AR of charge-neutral multiexcitons by measuring the biexciton lifetime (t X X) as a function of the NC size and doping configuration. We show that this method can be used to determine the presence of free carriers for any doped NC system, regardless of the presence/absence of defect channels in the carrier dynamics. Second, we develop a photophysical fitting model to determine the Auger lifetime of the simplest charged states in Si NCs: the negative (t X - ) and positive (t X + ) trions. Trion lifetimes shorten with increasing quantum confinement, as expected from (1) closer spatial proximity of the interacting charges and (2) increased relaxation of the momentum conservation rule. While both t X - and t X + are in the nanosecond time regime (and both therefore completely dominate the carrier dynamics), AR with excess holes is faster. This asymmetry is explained by a higher density of valence band states in comparison to the conduction band states, due to effective mass differences between electrons and holes.

36 MATERIALS SCIENCE↗

Topological solitonic macromolecules

Being ubiquitous, solitons have particle-like properties, exhibiting behaviour often associated with atoms. Bound solitons emulate dynamics of molecules, though solitonic analogues of polymeric materials have not been considered yet. Here we experimentally create and model soliton polymers, which we call “polyskyrmionomers”, built of atom-like individual solitons characterized by the topological invariant representing the skyrmion number. With the help of nonlinear optical imaging and numerical modelling based on minimizing the free energy, we reveal how topological point defects bind the solitonic quasi-atoms into polyskyrmionomers, featuring linear, branched, and other macromolecule-resembling architectures, as well as allowing for encoding data by spatial distributions of the skyrmion number. Application of oscillating electric fields activates diverse modes of locomotion and internal vibrations of these self-assembled soliton structures, which depend on symmetry of the solitonic macromolecules. Our findings suggest new designs of soliton meta matter, with a potential for the use in fundamental research and technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modeling and projecting implosion performance for the National Ignition Facility

Steady progress is being made in inertial confinement fusion experiments at the National Ignition Facility (NIF). Nonetheless, substantial further progress is still needed to reach the ultimate goal of fusion ignition. Closing the remaining gap will require either improving the quality of current implosions, increasing the implosion scale (and correspondingly the energy delivered by NIF), or some combination of the two. But how much of an improvement in implosion quality or energy scale is required to reach ignition? To reliably answer this question, an accurate understanding of current and past experiments is first required. Previous modeling efforts of NIF implosions have shown the need to resolve a wide range of scales (from microns to millimeters) as well as a faithful representation of the genuinely three-dimensional (3D) character of the stagnation process. Modeling NIF implosions is further complicated by the many perturbation sources that have been found to influence integrated implosion performance: flux asymmetries from the surrounding hohlraum, engineering features such as support tents and fill tubes, surface defects and contaminants, and more recently the radiation shadow cast by the fill tube on the capsule. A model including all of these effects, and with adequate resolution, challenges current computing capabilities but has recently become feasible on the largest computers. Here, we review the status of these multi-effect, 3D simulations of NIF implosions, their comparison to experimental data, and preliminary results on scaling these simulations to the threshold of ignition on NIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

In-Situ Transmission Electron Microscopy Study of the Evolution of Extended Defects in Oxide Nuclear Fuels

In-situ transmission electron microscopy (TEM) with simulated extreme environments is an effective tool for understanding and tracking microstructural changes down to the atomic scale. The objective of this research is to study the effect of temperature on the evolution of extended defects in ThO2 and UO2. Here, we present in-situ TEM isochronal thermal annealing experiments using a micro-electro-mechanical-system (MEMS)-based heating holder. ThO2 and UO2 single crystal specimens were grown inside an inert silver ampoule using hydrothermal synthesis. Both samples were irradiated using 2 MeV protons at 600oC up to 0.1 dpa at Texas A&M University’s Accelerator Laboratory. Fig. 1a shows a weak-beam dark field TEM image of ThO2 after irradiation, indicating the presence of faulted 1/3 <111> type dislocation loops. This presentation will discuss the effect of annealing temperature (600oC, 800oC, 1000oC, 1100oC, etc.) on dislocation loop density, size and distribution, loop nature (interstitial/vacancies) and Burgers vector, as well as the formation of voids in both ThO2 and UO2. This work will also discuss the interaction between defects during annealing. The in-situ TEM annealing cycle is shown in Fig 1b. This research significantly improves the understanding of defect behavior in oxide nuclear fuels with temperature and will aid computational modeling efforts. This work was supported as part of the Center for Thermal Energy Transport under Irradiation (TETI) Energy Frontier Research Center, funded by the U.S. Department of Energy Office of Science.

36 MATERIALS SCIENCE↗

Deep learning of accurate force field of ferroelectric HfO 2

The discovery of ferroelectricity in HfO 2 -based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density nonvolatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials are often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network–based interatomic force field of HfO 2 learned from ab initio data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. Here, the validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO 2 with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO 2 to related material systems including dopants and defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Neutron studies of gauge field and charge in Ih heavy-water ice

The distinctive character of water ice results from the partially disordered combination of covalent and hydrogen bonds in the network of hydrogen and oxygen atoms. The nontrivial hydrogen correlations we report in diffuse neutron scattering are analytically fit via a description of this state as a topological system exhibiting an emergent gauge field. This enables the density of correlation-terminating point defects to be decided as one defect per 500 oxygen sites at 30 K. Application of an analytical model of ice paves the way towards a detailed understanding of this ubiquitous solid.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗